AutoQuotes

Before implementing Akeneo, AutoQuotes relied on a homegrown product data management system that could no longer keep pace with the company’s growing scale and evolving technical requirements. 

As their catalog expanded and customer expectations increased, the limitations of this system became more pronounced; particularly in its lack of self-service capabilities and its inability to enforce consistent data governance. Teams struggled to maintain control over how data was managed and transferred, making it difficult to ensure accuracy, consistency, and compliance across a rapidly growing dataset.

At the same time, much of the work required to enrich and update product information remained highly manual. Managing large-scale updates meant editing product data one-by-one, creating significant inefficiencies and increasing the risk of errors. 

This manual burden was compounded by the need to meet aggressive turnaround expectations, with AutoQuotes committed to delivering updates within a 15-day window regardless of volume. Without scalable processes or automation in place, the team faced mounting pressure to maintain both speed and quality, highlighting the need for a more robust, flexible solution.

After implementing Akeneo PIM with the support of Akeneo partner Sitation, AutoQuotes was able to replace manual, fragmented processes with a more structured and scalable approach to product data management. 

By introducing standardized, rules-driven workflows and bulk update capabilities, the team gained greater control over how product information is enriched, validated, and distributed, reducing reliance on time-consuming manual tasks and enabling stronger governance that enures that data remains consistent, accurate, and aligned with internal standards.

Beyond initial implementation, AutoQuotes has continued to evolve its use of the platform to drive ongoing improvements in efficiency and quality. Enhanced validation processes and improved error visibility have made it easier for teams to identify and correct issues quickly, supporting faster update cycles and greater confidence in the data being delivered to customers. 

At the same time, Akeneo has provided a foundation for innovation, with AutoQuotes beginning to incorporate AI-powered capabilities to support product description and specification generation, positioning the business to scale its operations and continuously optimize performance over time.

The Result: A recipe for scalable, high-quality product data and efficiency

Remember how we said bad product data has a hidden compounding cost? Well, so does good product data, because the measurable improvements as a result of AutoQuotes’ usage of Akeneo PIM, truly speak for themselves:

• 71% decline in cost per enriched product SKU, showing a sustained reduction in enrichment costs over time.
• 55% increase in the volume of enriched products and updates completed, surpassing pre-Akeneo output levels.
• 50% reduction in manual product creation work, driven by bulk updates and rules-based changes.
• Higher output despite a 30%+ reduction in team size, with update volumes exceeding historical rates even when the team was fully staffed.

Even the team has stated how their overall task and validation cycles are “significantly faster”, validating “almost 16,000 products” in a single day. 

Congratulations to AutoQuote for winning the 2026 Growth Architect Award!